The Centers for Medicare & Medicaid Services (CMS) changed the way hospitals interact with patients when it implemented a pay-for-performance (P4P) system. Under this system, a financial reward or penalty is based in part on measures of patient experience. The program seeks to reward healthcare providers who expand their focus from solely delivering a highly technical set of services that improves the patient's health to creating an atmosphere that makes hospitalization more humane and respectful of patients' values and preferences. Refocusing priorities requires capital investment in more "patient-friendly" facilities or funding staff training programs. This study seeks to determine whether a relationship exists between inpatient costs and the score for "overall rating of hospital" (ORH) on the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) hospital version survey. Second, if a relationship exists, the study examines how that relationship changed during the time of CMS' implementation of its P4P program. The study's findings suggest that higher-cost hospitals have higher levels of positive patient experiences, after controlling for other variables. Importantly, the research findings indicate that hospitals are becoming more efficient in delivering care associated with higher levels of patient experience, coinciding with implementation of the P4P program.
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BMC Health Serv Res
January 2025
Department of Health Informatics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Background: Continuing Professional Development (CPD) is provided through in-service programs organized based on competency development and lifelong learning for healthcare professionals to stay fit with the required knowledge and skills. However, healthcare professionals' financial constraints and tight schedules sending them away from the workplace for CPD training is a challenge. eLearning is becoming the best solution to overcome those barriers and create accessible, efficient, flexible, and convenient professional development.
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January 2025
Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in Obstetrics, Beijing, 100191, China.
Background: Postpartum hemorrhage (PPH) is the leading cause of maternal mortality worldwide, with uterine atony accounting for approximately 70% of PPH cases. However, there is currently no effective prediction method to promote early management of PPH. In this study, we aimed to screen for potential predictive biomarkers for atonic PPH using combined omics approaches.
View Article and Find Full Text PDFAccurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI) advances, particularly convolutional neural networks (CNNs), have significantly improved diagnostic capabilities and accuracy by enabling the automated analysis of medical images.
View Article and Find Full Text PDFNPJ Precis Oncol
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Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, UK.
Histopathology foundation models show great promise across many tasks, but analyses have been limited by arbitrary hyperparameters. We report the most rigorous single-task validation study to date, specifically in the context of ovarian carcinoma morphological subtyping. Attention-based multiple instance learning classifiers were compared using three ImageNet-pretrained encoders and fourteen foundation models, each trained with 1864 whole slide images and validated through hold-out testing and two external validations (the Transcanadian Study and OCEAN Challenge).
View Article and Find Full Text PDFNPJ Digit Med
January 2025
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Monitoring fluid intake and output for congestive heart failure (CHF) patients is an essential tool to prevent fluid overload, a principal cause of hospital admissions. Addressing this, bladder volume measurement systems utilizing bioimpedance and electrical impedance tomography have been proposed, with limited exploration of continuous monitoring within a wearable design. Advancing this format, we developed a conductivity digital twin from radiological data, where we performed exhaustive simulations to optimize electrode sensitivity on an individual basis.
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